Buildings produce a large share of New York's greenhouse gas emissions, but predicting future energy demand—essential for ...
The XGBoost model predicts hyperglycemia risk in psoriasis patients with high accuracy, achieving an AUC of 0.821 in the training set. A web-based calculator was developed to facilitate personalized ...
When pitching the use of a model, data scientists rarely report on its potential value. They then experience an unnerving ...
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AI trained on sleep data predicts future disease and mortality years in advance
The SleepFM model reveals how sleep analysis can predict disease risk, offering insights into sleep's role as a vital health ...
Princeton researchers have developed a new tool to speed the discovery of advanced materials known as metal organic ...
Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...
Background Annually, 4% of the global population undergoes non-cardiac surgery, with 30% of those patients having at least ...
This important study introduces a new biology-informed strategy for deep learning models aiming to predict mutational effects in antibody sequences. It provides solid evidence that separating ...
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AI model can predict a person's disease risk using sleep data
A poor night's sleep portends a bleary-eyed next day, but it could also hint at diseases that will strike years down the road ...
In the past decade, cloud-scale analytics tools have transformed the digital fight against deforestation. Instead of manual reviews of satellite images taking multiple months, land-use change can ...
A new machine learning tool developed at Princeton will enable researchers to sift through trillions of design options to predict which metal organic framework will be useful in laboratories or ...
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